code: def test_input_labelstudio_video():
      """Test creation of LabelStudioVideoClassificationInput from video."""
      download_data(
          "https://label-studio-testdata.s3.us-east-2.amazonaws.com/lightning-flash/video_data.zip"
      )
      data = {
          "data_folder": "data/upload/",
          "export_json": "data/project.json",
          "multi_label": True,
      }
  
      train = LabelStudioVideoClassificationInput(
          RunningStage.TRAINING, data
      )
      assert train.data._labeled_videos[0] == (
          "data/upload/INO_Crossroads.avi",
          {"label": 0},
      )
      sample_iter = iter(train)
      sample = next(sample_iter)
      assert train
      assert sample
  
file_path: lightning-flash/tests/core/integrations/labelstudio/test_labelstudio.py
imports: import pytest
  from flash.core.data.utils import download_data
  from flash.core.integrations.labelstudio.input import LabelStudioImageClassificationInput, LabelStudioInput, LabelStudioTextClassificationInput, _load_json_data
  from flash.core.integrations.labelstudio.visualizer import launch_app
  from flash.core.utilities.imports import _TOPIC_CORE_AVAILABLE, _TOPIC_IMAGE_AVAILABLE, _TOPIC_TEXT_AVAILABLE, _TOPIC_VIDEO_AVAILABLE
  from flash.core.utilities.stages import RunningStage
  from flash.image.classification.data import ImageClassificationData
  from flash.text.classification.data import TextClassificationData
  from flash.video.classification.data import LabelStudioVideoClassificationInput, VideoClassificationData
label_desc: Use image node_id 8 for calling a global function with example usage: test_input_labelstudio_video() without return types